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20242026
most citedAlpaca against Vicuna: Using LLMs to Uncover Memorization of LLMs

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CR2026

Hidden in Thought: Transferable Chain-of-Thought Artifacts Induce Harmful Behavior

Ali khalil, Aly M. Kassem, Mohamed Abdelrazek +3

We investigate whether harmful chain-of-thought (CoT) traces from compromised language models can transfer unsafe behaviour and be distilled into reusable jailbreak attacks. Using…

cs.AI2026

Shared Latent Structures Enable Unified Backdoor Detection and Mitigation in LLMs

Omar Mahmoud, Aly M. Kassem, Thommen George Karimpanal +4

Backdoor attacks in large language models (LLMs) are often treated as isolated trigger-response failures, motivating defenses tailored to specific triggers or behaviors. We show th…

cs.CL2025

The Unintended Trade-off of AI Alignment:Balancing Hallucination Mitigation and Safety in LLMs

Omar Mahmoud, Ali Khalil, Buddhika Laknath Semage +2

Hallucination in large language models (LLMs) has been widely studied in recent years, with progress in both detection and mitigation aimed at improving truthfulness. Yet, a critic…

cs.CL2025

Improving Multilingual Language Models by Aligning Representations through Steering

Omar Mahmoud, Buddhika Laknath Semage, Thommen George Karimpanal +1

This paper investigates how Large Language Models (LLMs) represent non-English tokens -- a question that remains underexplored despite recent progress. We propose a lightweight int…

cs.CL2024★ 1 cited

Alpaca against Vicuna: Using LLMs to Uncover Memorization of LLMs

Aly M. Kassem, Omar Mahmoud, Niloofar Mireshghallah +5

In this paper, we introduce a black-box prompt optimization method that uses an attacker LLM agent to uncover higher levels of memorization in a victim agent, compared to what is r…